Efficient Meshy Neural Fields for Animatable Human Avatars

Abstract

Figure 1: EMA efficiently and jointly learns canonical shapes, materials, and motions via differentiable inverse rendering in an end-to-end manner. The method does not require any predefined templates or riggings. The derived avatars are animatable and can be directly applied to the graphics renderer and downstream tasks. All figures are best viewed in color.